/// <summary>
/// Gets the log-probability density function (pdf) for
/// this distribution evaluated at point <c>w</c>.
/// </summary>
///
/// <param name="x">A single point in the distribution range.</param>
///
/// <returns>
/// The logarithm of the probability of <c>x</c>
/// occurring in the current distribution.
/// </returns>
///
/// <remarks>
/// The Probability Density Function (PDF) describes the
/// probability that a given value <c>x</c> will occur.
/// </remarks>
///
protected internal override double InnerLogProbabilityDensityFunction(double x)
{
if (this.exact)
{
return(Math.Log(count(x, table)) - Math.Log(table.Length));
}
return(approximation.LogProbabilityDensityFunction(x));
}
/// <summary>
/// Not supported.
/// </summary>
///
public override double LogProbabilityDensityFunction(double x)
{
if (x <= 0 || x >= 1)
{
return(Double.NegativeInfinity);
}
double z = g(x);
return(normal.LogProbabilityDensityFunction(z));
}
/// <summary>
/// Gets the log-probability density function (pdf) for
/// this distribution evaluated at point <c>x</c>.
/// </summary>
/// <param name="x">A single point in the distribution range.</param>
/// <returns>The logarithm of the probability of <c>x</c>
/// occurring in the current distribution.</returns>
/// <remarks>The Probability Density Function (PDF) describes the
/// probability that a given value <c>x</c> will occur.</remarks>
protected internal override double InnerLogProbabilityDensityFunction(double x)
{
double z = g(x);
return(normal.LogProbabilityDensityFunction(z));
}
public void LogProbabilityDensityFunctionTest()
{
double x = 3;
double mean = 7;
double dev = 5;
NormalDistribution target = new NormalDistribution(mean, dev);
double expected = System.Math.Log(0.0579383105522966);
double actual = target.LogProbabilityDensityFunction(x);
Assert.IsFalse(double.IsNaN(actual));
Assert.AreEqual(expected, actual, 1e-15);
}
/// <summary>
/// Not supported.
/// </summary>
///
public override double LogProbabilityDensityFunction(double x)
{
return(normal.LogProbabilityDensityFunction(g(x)));
}
